Small-Molecule Modulators of Listeria monocytogenes Biofilm Development
Bibliographic record
Abstract
Listeria monocytogenes is an important food-borne pathogen whose ability to form disinfectant-tolerant biofilms on a variety of surfaces presents a food safety challenge for manufacturers of ready-to-eat products. We developed here a high-throughput biofilm assay for L. monocytogenes and, as a proof of principle, used it to screen an 80-compound protein kinase inhibitor library to identify molecules that perturb biofilm development. The screen yielded molecules toxic to multiple strains of Listeria at micromolar concentrations, as well as molecules that decreased (≤ 50% of vehicle control) or increased (≥ 200%) biofilm formation in a dose-dependent manner without affecting planktonic cell density. Toxic molecules-including the protein kinase C antagonist sphingosine-had antibiofilm activity at sub-MIC concentrations. Structure-activity studies of the biofilm inhibitory compound palmitoyl-d,l-carnitine showed that while Listeria biofilm formation was inhibited with a 50% inhibitory concentration of 5.85 ± 0.24 μM, d,l-carnitine had no effect, whereas palmitic acid had stimulatory effects. Saturated fatty acids between C(9:0) and C(14:0) were Listeria biofilm inhibitors, whereas fatty acids of C(16:0) or longer were stimulators, showing chain length specificity. De novo-synthesized short-chain acyl carnitines were less effective biofilm inhibitors than the palmitoyl forms. These molecules, whose activities against bacteria have not been previously established, are both useful probes of L. monocytogenes biology and promising leads for the further development of antibiofilm strategies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".